Inclusively Studying Inclusion: Centering Three Modes of Student Partnership in Assessing Equity and Inclusion in an Academic Department
Notice bibliographique
Résumé
In the 2019-20 academic year, two fourth-year students (Nicole and Loops) partnered with a professor (Ben) to explore questions of inclusion, equity, and diversity within the Haverford College psychology department.Our goal was to translate what we felt we knew from our lived experiences as students-that our academic experiences were not equitableinto quantitative and qualitative data to drive conversations of equity and inclusion forward with faculty in the department and the institution overall.The project culminated early in the pandemic in May 2020, but we continued to meet virtually-nearly weekly at times-beyond then.Going into the 2020-21 academic year, these conversations became about the relevance of our project for the conversations about diversity, inclusion, and antiracism that had intensified at Haverford College, culminating in a student strike that fall.Two questions guided our reflective discussions: what did we accomplish and, perhaps more importantly, how did we accomplish it?This latter question led to our current reflection.Our cooperative efforts were rooted in partnership at every level.We came together as student-faculty partners, our exploration was grounded in discussions with fellow studentsstudent-student partnerships-and our work was leveraged in collaborations with the institution-student-institution partnership.In this reflection, we describe how redefining student partnerships was central in developing and implementing a survey to assess inclusion, equity, and diversity within an academic department at a small liberal arts college.As we continued to meet to discuss our project and the current situation at Haverford and beyond, we wanted to narrate our work to better understand the process and demonstrate the possibilities of conducting research using a partnership model.When we started writing this reflective essay, we did not have a particular starting point, especially as we were pushed out of our comfort zones with writing centered around our lived experiences rather than the data collected.We each drafted preliminary ideas which developed into a brief abstract where we first detailed the idea of the three forms of partnership.We continued writing independently in response to reflective essay prompts and continued coming together to discuss questions and next steps, eventually bringing us to a cohesive essay.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,038 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,011 | 0,014 |
| Communication savante | 0,017 | 0,010 |
| Science ouverte | 0,003 | 0,039 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».